Firebase Data Connect
Firebase's first relational database solution for developers who want to create secure and scalable apps with Cloud SQL for PostgreSQL and type-safe mobile and web SDKs.Learn more.
Firebase Data Connect is a relational database service for mobile and webapps that lets you build and scale using a fully-managed PostgreSQLdatabase powered by Cloud SQL. It provides secure schema, query andmutation management using GraphQL technology that integrates well withFirebase Authentication. You can quickly integrate this product into your mobile andweb apps with SDK support in Kotlin Android, iOS, Flutter, and web.
Data Connect lets you declare your application's data model and theexact queries needed by your application. Using your data model we automaticallycreate a PostgreSQL database schema to fit your data model, secure serverendpoints that talk to the database, and type-safe SDKs for your clientapplication that talk to the server endpoints. It's like a "self-driving appserver" made-to-order for your specific application.
Key capabilities
| Backed by Cloud SQL for PostgreSQL | Rely on a fully-managed database service that helps you set up, maintain, manage, and administer your PostgreSQL relational databases on Google Cloud. |
| Vector search | Data Connect supports vector search for developers to build AI-powered applications. |
| Multiple platform SDKs | Firebase Data Connect offers multi-platform SDKs, for Kotlin Android, iOS, Flutter, and web. |
| User-based authentication | Data Connect supports end-user authentication, ensuring that only authorized users can access the data. |
| Visual Studio Code extension | Offers easy schema development, and query and mutation management, directly from your Visual Studio Code editor using GraphQL. |
| Emulator | Firebase Data Connect includes an emulator that lets you test your app with a local database without having to deploy to production. |
| AI assistance from Gemini inFirebase | Use Gemini inFirebase to generate queries and mutations on-demand using natural language and test them directly in theFirebase console. Learn more atUseAI assistance forData Connect for queries and mutations. |
How does it work?
The top-level resource forFirebase Data Connect is aservice, whichrepresents a managed GraphQL API that can be defined by developers and called byend users. Yourschema is the app data model for a service, representedprimarily as a collection of GraphQL source files, as well as specificconfiguration for attached datasources (such as Cloud SQL instances). There canbe only one schema per service. Finally, yourconnectors are collections ofqueries and mutations that have been defined to operate against a service'sschema. There can be many connectors per service (for instance if you have a"rider" app and a "driver" app for your rideshare company).
YourData Connect schema maps explicitly to a specific underlyingPostgreSQL database schema.Data Connect includes tooling toautomatically generate the SQL DDL needed to perform schema migrations based onchanges to the app schema. Based on your app schema,Data Connectautomatically generates additional GraphQL schema to query and manipulate thedata model.
Once your app schema is defined, you can write predefined queries and mutationsthat are executed to read and write data in the application.Data Connect queries and mutations are not submitted by client codeand executed on the server. Instead, when deployed, theseData Connectoperations are stored on the server, like Cloud Functions. This simplifies codemanagement, and development of your client code. In privileged environments,like theFirebase console and using our Data Connect VS Code extension,you can execute ad hoc operations with appropriate Google IAM credentials foradministrative operations.
For client code, each supported platform has acore SDK that handlesconnecting to the backend, issuing requests, and processing responses. TheseSDKs are not schema-aware and must be supplied with operation names andvariables as unstructured data. Each supported platform also has agenerated SDK. As you define your data model and operations, tooling on yourmachine will automatically generate strongly-typed SDKs specific to theapplication. These SDKs will "wrap" the core SDKs for type safety, ergonomics,and other features such as data validation and more down the road.
Implementation path
| Prototype your schema | Prototype your database schema, including designs using vector types, starting in a local environment with tooling | |
| Prototype your operations | Build predefined query and mutation operations for client apps based on automatically-generated queries and mutations | |
| Generate type-safe SDKs | Generate and test type-safe SDKs from your schema and operations, then implement client-side code | |
| Deploy schema and operations | Deploy the schema and operations for yourFirebase Data Connect service | |
| Deploy clients | Deploy your client code |
Next steps
- Try outData Connect right now: explore a quickstart app repositoryand build a fully-featuredData Connect app by following ourcodelab for web,codelab for iOS, orcodelab for Android.
- If you'd like to see theFirebase Data Connect development flow in action,read through theGet started guide.
- Learn aboutData Connectpricing and billing.
Except as otherwise noted, the content of this page is licensed under theCreative Commons Attribution 4.0 License, and code samples are licensed under theApache 2.0 License. For details, see theGoogle Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2026-01-21 UTC.